There are eight evidence types, as discussed in the previous eight sections,
and a single integrated plausibility value needs to be computed from them.
All values are assumed to be on the same scale so this simplifies
the considerations.

If there is no property, description or subcomponent evidence, then
evidence integration produces no result.

Other relationship evidence should be incremental, but not overwhelmingly so.

Only types with evidence are used
(i.e. some of the evidence types may not exist, and so should be ignored).

Property, description and subcomponent evidence are complementary in
that they all give explicit evidence for the object and all should be
integrated.

If supercomponent evidence is strong, then this gives added
support for a structure being a subcomponent.
Weak supercomponent evidence has no effect, because the subcomponent
could be there by itself, or not be there at all.

If superclass evidence is strong, then this gives added support for
the object.

Strong association evidence supports the possibility of an object's
presence.

If other identities are competing, they reduce the plausibility.

As subclasses imply objects, the plausibility of an object
must be at least that of its subclasses.

Based on these constraints, the following integration computation has been designed:

Let:

be the eight evidence values, with weightings:

Then:

if

then

else

if

then

else

if

then

else

if

then

else

Finally, the integrated plausibility is:

The and terms in the final function ensure the result is in the
correct range.
The weighting constants (0.1 and ) used above were chosen
to influence but not dominate the evidence computation and were found
empirically.
Small changes (e.g. by 10%) do not affect the results.

The invocation network fragment executing this function is similar
to those previously shown except for the use of a "gated-weight" function
unit that implements the evidence increment function for supercomponent,
association, superclass and inhibition evidences.